How to Use the Twelve Data MCP in Google ADK

Q: Can I use Twelve Data to analyze crypto pairs with Google ADK?

Yep. Start by calling getcryptolist to see what's available, then run other pricing tools across the agent flow. The data is just as accessible whether it's stock or crypto.

Q: What type of financial data does Twelve Data provide for Google ADK?

It provides historical OHLCV candle data via gettimeseries, along with forex rates and commodity prices. All this pricing data is structured to work well in BigQuery.

Q: What if I need currency conversion using Twelve Data with Google ADK?

You can use the convertcurrency tool. This lets your agent convert an amount between currencies, keeping multi-national financial data consistent for analysis.

Build enterprise financial agents on Google ADK. Actionable data from Twelve Data, integrated into BigQuery.

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Connect Twelve Data MCP to Google ADK

Create your Vinkius account to connect Twelve Data to Google ADK and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Twelve Data with Google ADK

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Get Real-Time Pricing Data

To get the current stock price, call `get_quote`. The result is fed directly into your agent's reasoning process. Because of native integration with BigQuery, this data can act on your existing enterprise datasets. If you need speed over completeness, use `get_real_time_price`. It delivers a lightweight quote suitable for large-scale analysis across Google Cloud infrastructure.

Analyze Market Trends

You can identify market conditions using technical indicators like the RSI. When you call `get_rsi`, your agent determines if assets are overbought or oversold, helping guide complex decision-making. For momentum analysis, use `get_macd`. This tool calculates Moving Average Convergence Divergence, giving Gemini models a solid data point to work with in their long-context reasoning.

List and Search Instruments

Need to find an asset? Run `search_symbols` specifying the instrument type or exchange. This ensures your agent targets exactly what you want within your BigQuery schema. Listing available stocks is simple with `get_stock_list`. You can filter by exchange, giving you a controlled list of options before running any complex queries on the MCP Server.

Setup guide

Set up Twelve Data MCP in Google ADK

Prerequisites

Python 3.10+ installed
google-adk package (pip install google-adk)
Active Vinkius subscription with a valid endpoint token

1

Install Google ADK

Run pip install google-adk to install the Agent Development Kit. MCP support is included via the McpToolset class.
2

Connect via SSE transport

Use McpToolset.from_server() with SseServerParams pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create an LlmAgent

Pass the returned mcp_tools list directly to LlmAgent(tools=mcp_tools). The ADK maps each MCP tool to a native Gemini function call — no manual schema definitions required.
4

Run with any Gemini model

The agent works with any Gemini model (gemini-2.0-flash, gemini-2.5-pro, etc.). Copy the full example on the right to get started with Twelve Data tools in your ADK agent.

agent.py

from google.adk.agents import LlmAgent
from google.adk.tools.mcp_tool.mcp_toolset import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import SseServerParams

# Connect to the MCP via SSE
mcp_tools, exit_stack = await McpToolset.from_server(
    connection_params=SseServerParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    )
)

# Create your agent with auto-discovered tools
agent = LlmAgent(
    name="Twelve Data_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Twelve Data tools via MCP.",
    tools=mcp_tools,
)

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Common questions about Twelve Data MCP in Google ADK

The agent framework supports calling the MCP Server directly. This means your Gemini models can pull real-time data, like a quote from `get_quote`, and act on it within the Google Cloud environment.

Yep. Start by calling `get_crypto_list` to see what's available, then run other pricing tools across the agent flow. The data is just as accessible whether it's stock or crypto.

It provides historical OHLCV candle data via `get_time_series`, along with forex rates and commodity prices. All this pricing data is structured to work well in BigQuery.

You can use the `convert_currency` tool. This lets your agent convert an amount between currencies, keeping multi-national financial data consistent for analysis.

Yes. The server is designed to handle structured calls from large models like Gemini and can provide necessary data points, such as `get_exchange_rate`, reliably for your enterprise workflow.

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